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Creating a Phrase Similarity Graph from Wikipedia

机译:从维基百科创建短语相似度图

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The paper addresses the problem of modeling the relationship between phrases in English using a similarity graph. The mathematical model stores data about the strength of the relationship between phrases expressed as a decimal number. Both structured data from Wikipedia, such as that the Wikipedia page with title "Dog" belongs to the Wikipedia category "Domesticated animals", and textual descriptions, such as that the Wikipedia page with title "Dog" contains the word "wolf" thirty one times are used in creating the graph. The quality of the graph data is validated by comparing the similarity of pairs of phrases using our software that uses the graph with results of studies that were performed with human subjects. To the best of our knowledge, our software produces better correlation with the results of both the Miller and Charles study and the WordSimilarity-353 study than any other published research.
机译:该论文解决了使用相似度图对英语中短语之间的关系进行建模的问题。数学模型存储有关以十进制数表示的词组之间的关系强度的数据。既来自Wikipedia的结构化数据(例如,标题为“ Dog”的Wikipedia页面属于Wikipedia类别“驯养的动物”),也包括文本描述,例如标题为“ Dog”的Wikipedia页面包含单词“ wolf” 31时间用于创建图形。通过使用我们使用该图的软件将短语对的相似性与对人类受试者进行的研究结果进行比较,可以验证图数据的质量。据我们所知,我们的软件与Miller和Charles研究以及WordSimilarity-353研究的结果相比,具有比其他任何已发表的研究更好的关联性。

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